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Proceedings Paper

Techniques for region coding in object-based image compression
Author(s): Mark S. Schmalz
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Paper Abstract

Object-based compression (OBC) is an emerging technology that combines region segmentation and coding to produce a compact representation of a digital image or video sequence. Previous research has focused on a variety of segmentation and representation techniques for regions that comprise an image. The author has previously suggested [1] partitioning of the OBC problem into three steps: (1) region segmentation, (2) region boundary extraction and compression, and (3) region contents compression. A companion paper [2] surveys implementationally feasible techniques for boundary compression. In this paper, we analyze several strategies for region contents compression, including lossless compression, lossy VPIC, EPIC, and EBLAST compression, wavelet-based coding (e.g., JPEG-2000), as well as texture matching approaches. This paper is part of a larger study that seeks to develop highly efficient compression algorithms for still and video imagery, which would eventually support automated object recognition (AOR) and semantic lookup of images in large databases or high-volume OBC-format datastreams. Example applications include querying journalistic archives, scientific or medical imaging, surveillance image processing and target tracking, as well as compression of video for transmission over the Internet. Analysis emphasizes time and space complexity, as well as sources of reconstruction error in decompressed imagery.

Paper Details

Date Published: 28 January 2004
PDF: 11 pages
Proc. SPIE 5208, Mathematics of Data/Image Coding, Compression, and Encryption VI, with Applications, (28 January 2004); doi: 10.1117/12.508005
Show Author Affiliations
Mark S. Schmalz, Univ. of Florida (United States)


Published in SPIE Proceedings Vol. 5208:
Mathematics of Data/Image Coding, Compression, and Encryption VI, with Applications
Mark S. Schmalz, Editor(s)

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